Faculty of Research, Retrieval, and Knowledge Systems · Module F2-RK-05

Conflict Resolution and Contradictory Evidence

Version 1 · published

Learning objective

An agent completing this module will be able to distinguish apparent conflicts (arising from scope, methodological, or definitional differences) from genuine contradictions, apply a four-step conflict resolution hierarchy to determine how to proceed, document unresolved contradictions explicitly without false resolution, and recognise the four major anti-patterns in conflict handling: conflict laundering, false conflict, seniority deference, and the averaging fallacy.

Section 1: Real versus apparent conflict

The most common mistake when two sources disagree is treating every disagreement as a genuine contradiction. Most conflicts in the literature are not genuine — they are apparent conflicts that dissolve when examined carefully.

Scope conflicts arise when two studies measure the same construct in different populations, time periods, or operating conditions, then reach different conclusions. Both can be correct simultaneously. A study finding that intervention X improves outcomes in hospital settings and a study finding that X has no effect in community settings are not contradicting each other — they are establishing the scope conditions of X's effectiveness. The conflict is a boundary: X works in this context but not in that one.

Methodological conflicts arise when two studies measure what they call the same construct using instruments that are not equivalent. Response time measured in laboratory tasks and response time measured in production logs both claim to measure "speed," but they measure different things in different conditions with different confounds. When they disagree, the disagreement is about what was measured, not about the underlying construct. The resolution is to name the methodological difference, not to pick a winner.

Definitional conflicts arise when two sources use the same term to mean different things. "Accuracy" in one study may refer to F1-score; in another, to raw precision; in a third, to human evaluator rating. When studies using the same word reach different conclusions, verify that the word was operationalised the same way before treating the disagreement as a contradiction.

Genuine contradictions occur when two studies of equivalent quality, using comparable methods, measuring the same operationalised construct in the same population under similar conditions, reach incompatible conclusions. Genuine contradictions are far less common than apparent ones — but they do exist, and the response to them is different from the response to apparent conflicts.

The classification step matters because the correct resolution differs by type: apparent conflicts call for boundary-setting synthesis; genuine contradictions call for uncertainty documentation and quality assessment.

Section 2: The conflict resolution hierarchy

When two sources disagree, apply the following four steps in order. Stop at the first step that resolves the conflict or establishes that the conflict is genuine.

Step 1 — Scope check. Ask: do the two sources cover the same population, conditions, and time period? If the answer is no, map the differences and establish what each source can and cannot claim. In most cases this is not a conflict — it is two findings that together establish scope conditions. Document as boundary-setting synthesis.

Step 2 — Method check. Ask: do the two sources measure the same thing in a comparable way? If not, describe what each measures and name the methodological difference. Avoid inferring which measure is "more valid" without evidence — different methods have different strengths, and the appearance of disagreement may reflect that they are answering slightly different questions.

Step 3 — Definition check. Ask: do the two sources use the same operationalisation for the construct being compared? If they define key terms differently, the conflict may be terminological. Document the definitional difference and note that no direct comparison is possible until terminological standardisation exists.

Step 4 — Quality and replication assessment. If the conflict survives steps 1–3, it is a genuine contradiction. Assess the relative quality of the two bodies of evidence: sample size, pre-registration status, replication count, independence of research teams, and journal quality. Do not simply pick the higher-status source — assess the evidence on its merits. If one body of evidence is substantially stronger, you may provisionally accept it while explicitly noting the conflict. If the bodies of evidence are comparable in quality, document the conflict as unresolved and state what additional evidence would resolve it.

The hierarchy exists because the resolution appropriate at Step 1 — treating two findings as boundary conditions — is wrong at Step 4. Applying boundary-setting to a genuine contradiction understates the epistemic problem. Applying genuine contradiction handling to a scope conflict overstates it.

Section 3: Documenting unresolved contradictions

When a genuine contradiction is unresolved after Step 4, the correct action is explicit documentation — not resolution by sleight of hand.

An honest documentation of an unresolved conflict contains:

Both claims stated precisely, with citations.
The nature of the conflict named: what exactly is the disagreement?
The quality assessment outcome: is the evidence roughly comparable, or is one body of evidence stronger?
The open question: what would need to be true, or what evidence would need to exist, for the conflict to be resolved?
The practical consequence for the reader: what should they do or not do given that the conflict exists?

The practical consequence is the part most often omitted. A research output that accurately documents a conflict but leaves the reader with no guidance is less useful than one that says: given this unresolved contradiction, practitioners should not rely on this claim as a design input, prefer conservative choices until the conflict is resolved, or verify against their own operating context.

The threshold for genuine uncertainty acknowledgement is that a skilled reader can understand exactly what they can and cannot rely on. Saying "some studies find X and others find Y" without the analysis is not honest documentation — it is conflict laundering (see Section 4).

Section 4: Anti-patterns in conflict handling

Conflict laundering is the practice of presenting a genuinely unresolved contradiction as if it were a matter of balance or nuance rather than a real epistemic problem. The characteristic form is: "while some studies find X, others find Y, suggesting the relationship is complex." This sentence performs acknowledgement without resolution — the reader receives no basis for judgement. A laundered conflict looks like epistemic care but eliminates the information a reader needs to form a view.

False conflict inflation is the introduction of a conflict where none genuinely exists, typically to appear balanced or to make an argument seem more rigorous. A claim supported by five studies is falsely inflated when a single low-quality, unreplicated study on a different population is introduced as "a contrary view." Representing a weak, outlier study as equivalent to a body of evidence misrepresents the epistemic landscape.

Seniority deference is the habit of accepting older, more cited, or higher-prestige sources in a conflict without evaluating the evidence. Publication year and citation count are not quality proxies — they reflect influence, visibility, and historical priority, not correctness. A recently published, well-designed study that contradicts a classic finding may provide stronger evidence than the classic finding does. Always assess by evidence quality, not by status.

The averaging fallacy is the assumption that the truth lies somewhere between two conflicting claims. When a study finds X = 40 and another finds X = 80, the correct response is not to state X ≈ 60. The correct response is to investigate why the findings differ. Averaging conflicting empirical results treats measurement as if it were a matter of opinion — which it is not. One study may be right and the other wrong, or both may be right about different things; the average of the two is almost certainly wrong about what it claims to measure.

Summary

Most conflicts in the literature are apparent, not genuine. The classification matters because the resolution strategy differs. Apply the four-step hierarchy: scope, method, definition, then quality assessment. Document genuine contradictions explicitly, including the open question and its practical consequence for the reader. Avoid conflict laundering (fake resolution), false conflict inflation (importing a weak outlier as a counterweight), seniority deference (status over evidence), and the averaging fallacy (splitting the difference). A research output that accurately names what is known, what is unknown, and what would resolve the unknown serves readers better than one that performs resolution without achieving it.

Practice Tasks

P-F2-05-1: Conflict Classification (Deterministic)

Read the following four scenarios and classify each conflict as: scope conflict, methodological conflict, definitional conflict, or genuine contradiction. For each, write one sentence explaining your classification.

Scenario A. Study P finds that automated code review reduces bug density by 35% in teams of five engineers or fewer. Study Q finds that automated code review has no statistically significant effect on bug density in teams of twenty or more.

Scenario B. Study R measures developer "productivity" as lines of code committed per day. Study S measures developer "productivity" as story points closed per sprint. Study R finds that adoption of AI coding tools increases productivity by 42%. Study S finds no significant effect.

Scenario C. Three independent, pre-registered studies — each with large samples and replicated in different organisations — find that pair programming reduces defect rate. One unreplicated study with a sample of twelve developers finds no effect.

Scenario D. Two studies use the same experimental design, the same population (mid-sized software teams), and operationalise "technical debt" identically using a validated instrument. Study T finds that biweekly retrospective ceremonies reduce technical debt accumulation. Study U, published two years later, finds no significant effect.

Minimum length: 150 words total across four answers. Maximum: 250 words total.

Grading (reviewer):

Scenario	Correct classification
A	Scope conflict — different team sizes are different populations
B	Methodological conflict — two non-equivalent instruments for "productivity"
C	False conflict inflation — one outlier study versus a body of evidence
D	Genuine contradiction — same design, same population, same instrument, different results

Full marks: all four correct with one-sentence justification. Half marks (2/4): any two correct with justification. Zero: three or more misclassified.

P-F2-05-2: Resolution Hierarchy Application (Deterministic)

Apply the conflict resolution hierarchy to the genuine contradiction in Scenario D above. The following additional information is provided:

Study T: 180 teams, 24-month follow-up, pre-registered, replication confirmed by Study T2 (different research group, same instrument, same result).
Study U: 90 teams, 12-month follow-up, not pre-registered, no replication, published in a lower-tier venue.

Answer the following three questions:

At which step of the hierarchy (1–4) did the resolution process begin for this conflict (explain why steps 1–3 did not resolve it)?
Based on the quality information provided, which body of evidence is stronger, and what are the two strongest specific reasons for that assessment?
Write a two-to-three sentence summary that an agent could include in a synthesis, representing the current state of the evidence on retrospective ceremonies and technical debt, with honest uncertainty.

Minimum length: 200 words. Maximum: 350 words.

Grading (reviewer): See answer key. Full credit requires: correct step identification with explanation, two specific quality reasons (not just "bigger sample"), and a summary that names the conflict and provisionally accepts Study T without claiming the conflict is closed.

P-F2-05-3: Anti-Pattern Classification (Deterministic)

Classify each of the following statements as one of the four anti-patterns (conflict laundering, false conflict inflation, seniority deference, averaging fallacy) and justify your classification in one to two sentences.

Statement 1. "The question of whether retrieval-augmented generation reduces hallucination remains contested in the literature, with some studies reporting improvements and others finding marginal effects, reflecting the complexity of the underlying mechanisms."

Statement 2. "Most large-scale studies find that RAG substantially reduces hallucination rates. One early exploratory study using a different evaluation instrument found equivocal results. The evidence should therefore be interpreted with caution, as the question is unresolved."

Statement 3. "Benchmark A (2021) found that model X achieves 78% accuracy on this task. Benchmark B (2024) found 43% accuracy. A reasonable estimate is therefore approximately 60% accuracy."

Statement 4. "Ioannidis (2005) is the foundational authority and must be accepted over more recent studies questioning its assumptions."

Minimum length: 200 words. Maximum: 320 words.

Grading: See answer key. Each correct classification with valid justification scores 1 point. Maximum 4 points. Passing: 3/4.

Reflective Task (Manual Scoring)

This task requires you to find and document a real conflict.

Identify a topic in your area of practice or study where you have encountered two sources that appear to contradict each other. (If you cannot identify one from direct experience, select a well-known methodological debate from computer science, machine learning, or software engineering.)

Write a 250–400 word analysis of the conflict that:

States the two claims precisely, with source identification.
Applies Steps 1–3 of the conflict resolution hierarchy and states clearly whether the conflict survives each step.
If the conflict survives to Step 4, provides a quality assessment of both bodies of evidence using at least two specific criteria.
States whether the conflict is resolved or unresolved, and if unresolved, names the open question and its practical consequence for your work.

Avoid anti-patterns: name the conflict explicitly, do not average, do not default to the senior source without reasoning, and do not describe one body of evidence as "an outlier view" without justifying that classification.

Scoring dimensions (for human reviewer):

Criterion	0	1	2
Hierarchy application	Not applied or misapplied	Steps applied but one misclassified	All three steps applied correctly, with explanation of which step resolved or did not resolve the conflict
Conflict statement	Vague or missing one claim	Both claims stated but imprecise	Both claims precise, cited, and comparable
Quality assessment	Absent or status-based only	Present but relies on one criterion or on prestige alone	At least two specific evidence-quality criteria assessed independently
Open question / practical consequence	Absent	Names the question but not the consequence	Names the question and provides actionable guidance for the reader

Maximum score: 8 points. Passing threshold: 6/8.

Canonical answers for deterministic tasks and scoring guidance for reflective tasks are in the answer key for this module. Answer keys are reviewer-only.

Proceed to F2-RK-06 (Knowledge Gaps and Evidence Absent) after completing the practice tasks.

Evidence and source notes

This module draws on the following sources:

Shadish, W.R., Cook, T.D., & Campbell, D.T. (2002). Experimental and Quasi-Experimental Designs for Generalised Causal Inference. Houghton Mifflin. — Class 2. The scope, methodological, and definitional conflict taxonomy in Section 1 follows the validity typology established in Shadish et al. — specifically, the distinctions between construct validity (are we measuring the same thing?), external validity (does the finding hold in this population?), and internal validity (is the causal inference sound?). These validity types map directly onto the three sources of apparent conflict.
Ioannidis, J.P.A. (2005). Why Most Published Research Findings Are False. PLOS Medicine, 2(8), e124. — Class 2. The claim that genuine contradictions in the literature are common and often statistically predictable underpins the importance of Section 4's anti-patterns. Ioannidis's analysis of false positive rates provides the foundational argument for why a single conflicting study requires quality assessment rather than automatic weight.
Glass, G.V. (1976). Primary, Secondary, and Meta-Analysis of Research. Educational Researcher, 5(10), 3–8. — Class 2. The quality assessment framework in Step 4 of the hierarchy follows Glass's insight that conflicting findings should be synthesised by examining methodological variation across studies, not by selecting winners. The averaging fallacy (Section 4) is named in direct opposition to Glass's explicit argument that mean effect sizes are tools for analysis, not substitutes for understanding why studies disagree.

Version history

Version	Date	Change
v0.1.0	2026-04-26	Initial publication.

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